Edo Airoldi

Towards Stability and Optimality in Stochastic Gradient Descent

Iterative procedures for parameter estimation based on stochastic gradient descent (SGD) allow the estimation to scale to massive data sets. However, they typically suffer from numerical instability, while estimators based on SGD are statistically inefficient as they do not use all the information i…